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Vegetated coastal sand dunes can be vital components of flood risk reduction schemes due to their ability to act as an erosive buffer during storm surge and wave attack. However, the effects of plant morphotypes on the wave-induced erosion process are hard to quantify, in part due to the complexity of the coupled hydrodynamic, morphodynamic, and biological processes involved. In this study the effects of four vegetation types on the dune erosion process under wave action was investigated in a wave flume experiment. Sand dune profiles containing real plant arrangements at different growth stages were exposed to irregular waves at water levels producing a collision regime to simulate storm impact. Stepwise multivariate statistical analysis was carried out to determine the relationship of above- and below-ground plant variables to the physical response. Plant variables included, among others, fine root biomass, coarse root biomass, above-ground surface area, stem rotational stiffness, and mycorrhizal colonization. Morphologic variables, among others, included eroded sediment volume, cross-shore area centroid shift, and scarp retreat rate. Results showed that vegetation was able to reduce erosion during a collision regime by up to 37%. Although this reduction was found to be related to both above- and belowground plant structures and their effect on hydrodynamic processes, it was primarily accounted for by the presence of fine root biomass. Fine roots increased the shear strength of the sediment and thus lowered erosional volumes and scarp retreat rates. For each additional 100 mg/L of fine roots (dry) added to the sediment, the erosional volume was reduced by 6.6% and the scarp retreat rate was slowed by 4.6%. Coarse roots and plant-mediated mycorrhizal colonization did not significantly alter these outcomes, nor did the apparent enhancement of wave reflection caused by the fine roots. In summary, fine roots provided a unique ability to bind sediment leading to reduced dune erosion. 

Coastal risk reduction features are often built to protect infrastructure and ecosystems from damaging waves, sea level rise, and shoreline erosion. Engineers often use predictive numerical modeling tools, such as Delft3D to help design optimal intervention strategies. Still, their use by coastal managers for optimizing the design of living shorelines in complex geomorphic environments has been limited. In this study, the Delft3D modeling suite is used to help select the optimum living shoreline structure for a complex inlet and bay system at Carancahua Bay, Texas. To achieve this goal, an extensive array of sensors was deployed to collect hydrodynamic and geotechnical data in the field, and historical shoreline changes were assessed using image analysis. The measured data were then used to parameterize and validate the baseline Delft3D model. Using this validated model, the hydrodynamics resulting from a series of structural alternatives were simulated and compared. The results showed that the mouth of this complex inlet has widened greatly since the 1800s due to wave erosion and sea level rise. The analysis of the structural alternatives showed it was not advisable to attempt a return of the inlet to its historical extent, but rather to create a hybrid design that allowed for limited flow to continue through a secondary inlet. The numerical modeling effort helped to identify how to best reduce wave and flow energy. This study provides a template for the application of Delft3D as a tool for living shoreline design selection under complex shallow-estuary and inlet dynamics. 

Abstract Tropical cyclones play an increasingly important role in shaping ecosystems. Understanding and generalizing their responses is challenging because of meteorological variability among storms and its interaction with ecosystems. We present a research framework designed to compare tropical cyclone effects within and across ecosystems that: a) uses a disaggregating approach that measures the responses of individual ecosystem components, b) links the response of ecosystem components at fine temporal scales to meteorology and antecedent conditions, and c) examines responses of ecosystem using a resistance–resilience perspective by quantifying the magnitude of change and recovery time. We demonstrate the utility of the framework using three examples of ecosystem response: gross primary productivity, stream biogeochemical export, and organismal abundances. Finally, we present the case for a network of sentinel sites with consistent monitoring to measure and compare ecosystem responses to cyclones across the United States, which could help improve coastal ecosystem resilience.